nyu-mll/glue
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How to use autoevaluate/glue-mnli with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="autoevaluate/glue-mnli") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("autoevaluate/glue-mnli")
model = AutoModelForSequenceClassification.from_pretrained("autoevaluate/glue-mnli")This model is a fine-tuned version of distilbert-base-uncased on the glue dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.9378 | 1.0 | 625 | 0.7896 | 0.6585 |
| 0.7086 | 2.0 | 1250 | 0.7850 | 0.6712 |
| 0.5758 | 3.0 | 1875 | 0.8003 | 0.6772 |